Organizations, such as companies, as well as individuals, are increasingly subject to background checks. For example, employers commonly perform background checks on prospective employees to ensure that the information they are providing on resumes and employment applications is truthful, and to locate other information regarding the prospective employees to secure a full picture of them. Background checks may be performed on organizations and individuals for other reasons as well.
However, getting a sense of an organization or individual based on the information that is gathered can prove to be difficult, especially where a large number of organizations and/or individuals are to be processed. Users typically process data visually better than they do by reading words on a page, and yet most background checks provide only textual viewing of the information collected regarding a given person or organization. As such, gaps within the background of a given organization or individual may be difficult to discern, or may be missed entirely.
Furthermore, existing approaches to visualize data are often not well suited for visualizing background check information. These approaches may not display the data in a way that is meaningful to a user who is performing a background check on an individual or organization. In addition, such approaches may not be interactive, and instead provide users with a static and passive display of information that is not optimally helpful. For these and other reasons, therefore, there is a need for the present invention.